Month: September 2015

At Dreamforce, Michelle Huff, VP of Product Marketing at SFDC, noted the historical evolution of CRM from a system of record to a system of engagement. This shift reduced data entry and supported mobile, social, and account maintenance. SFDC is now evolving into a system of intelligence which enables account planning, account awareness, and recommendations from within the Sales Cloud. This evolution can be seen in enhancements to Data.com (my next post) and the newly launched SalesforceIQ for Small Business and SalesforceIQ for Sales Cloud services

The goal of SalesforceIQ is to shift CRM from relationship management to relationship intelligence while automating key activities and proactively suggesting tasks and making recommendations. Thus, if a prospect states in an email, “can we connect to discuss a contract?” SalesforceIQ flags the request and schedules it as a high priority task

The service is built on the 2014 acquisition of RelateIQ and mines emails, calendars, marketing apps, and other data sources to gather customer data. The service offers “smarter selling” through lead prioritization and relationship capital management (RCM) recommendations concerning contact introductions. The RCM feature is integrated into inboxes, mobile (Android, iOS), and Chrome apps.

Other mobile features include an integrated inbox with the CRM, email shortcuts to quickly enter common phrases, cloud storage integration, and a notifications feed. For users in Gmail on Chrome, a plug in ties Gmail back to SalesforceIQ and supports its tools from within the Chrome browser.

The new service “seeks out the patterns needed to provide insights into future outcomes and proactively recommends actions to build stronger relationships with customers and accelerate sales,” said Salesforce. “SalesforceIQ for Small Business manages deals, accelerates pipelines and proactively guides SMBs through every step of the sales process, allowing them to focus on closing deals and building 1:1 relationships with their customers.”

The Small Business service is generally available in the US, Canada, and Australia and is priced as low as $25 per user per month for up to five users. For $65 per user per month, the system provides potential introductions, CRM data in your Inbox, Sales and Activity reports, and direct integrations. SalesforceIQ is offering 14 day free trials. Pricing is based on annual contracts.

The Sales Cloud edition is currently free in beta with general availability in early 2016. Sales Cloud pricing will be announced at general availability. The beta version is English only with additional languages planned. The Sales Cloud version includes a new email app where “Salesforce is your Inbox” connected to the Sales Cloud. The system automatically associates emails with contacts. Users can create opportunities from the app, respond back to the prospect with macro-based comments, and schedule a meeting using the scheduling assistant.

“Today’s massive influx in communication data creates powerful signals about the health and potential of business relationships. It also creates a lot of noise,” said Steve Loughlin, CEO of SalesforceIQ, Salesforce. “With SalesforceIQ, companies can now make sense of this data and pull out insights to drive their businesses forward with intelligence.”

The service promises standard sales intelligence benefits including reduced time gathering data, smarter selling, and immediate benefits with no setup costs and easy onboarding. Along with RCM and opportunity prioritization, the service provides read receipts, suggested tasks, dynamic scheduling to improve calendaring, and shortcuts which “allow customers to quickly insert commonly used phrases to reduce time spent composing emails.”

It should be noted that SalesforceIQ is not prioritizing leads, but providing a set of recommended actions based upon the semantic mining of emails. Thus, the system evaluates whether a customer has asked a question or has been untouched for a while. Through machine learning, the system tailors recommendations based upon each reps’ style.

An Opportunities Intelligence report provides “instant visibility” into account status by providing metrics such as days in current status, inactive days, last communication date, and next follow up due date. A stream view provides “a centralized view of all communications between your team and the customer.” Users can leave comments in the stream and @reference coworkers for a quick response or follow up.

Calendaring is improved by a Chrome extension app that inserts free times into messages, manages the auto invite process with the customer or prospect, and creates the meeting in the user’s calendar.

Integration partners include MailChimp, Hubspot, and Pardot.

Beta customers include ClassPass and News Corp.

Jamie Grenney, VP of Marketing at predictive marketer Infer, commended Salesforce for implementing basic predictive tools into its product line noting that “these improvements will help Salesforce with product adoption for a large swath of its customers.” Grenney continued that the SalesforceIQ offering “only scratches the surface of what predictive can do” as it is limited to internal email and calendar data and lacks external data. “There are many other data sources that can provide important clues. These signals that go into a model are different from one company to the next. Without a solid understanding of a company’s process, their data, and what outcome they’re trying to predict, it is difficult or even dangerous to build custom-fit models. You run the risk of setting bad targets, overfitting models, and ultimately making the wrong recommendations.”

“SalesforceIQ is designed to capture inferential data from emails, meetings, and logged calls and then present intelligent suggestions and timely reminders for things like new meeting appointments and follow-up actions,” said Nancy Nardin of Smart Selling Tools. “I love the concept of using inferential data to eliminate time spent on searching for past activity for the purpose of formulating action plans and next steps. However, the solution has a long way to go before it can be wholly relied on.”

In short, SalesforceIQ sounds like a sales rep toolkit which offers small ways to improve rep efficiency and task awareness. It is not so much focused on surfacing new insights but in reducing task work, leveraging colleague relationships, and ensuring prospects do not fall between the cracks. As such, Salesforce is a baby step in the “System of Intelligence” evolution.

LinkedIn Posts lack discovery tools resulting in a rapid fall off from the first day peak.

One of the frustrating things about LinkedIn posts is the lack of a long-tail. Most posts peak within 48 hours and quickly die off. The above chart is indicative of a typical post’s life. If I were writing a gossip column or commenting on fluctuations in stock prices, such a pattern would be understandable; but I comment on the information industry so there is little reason that my ideas would have virtually no value to my followers after 72 hours. The problem is one of LinkedIn’s design. In their desire to be social, they forgot that good content needs to be discoverable.

The quick die off is due to several problems in LinkedIn design:

Posts generally come to reader’s attention via the update feed which means that it quickly moves down the reader’s list. Thus, being seen by any of your followers is basically a function of timing and luck. The writer is competing against LinkedIn’s author series, sponsored updates, other posters, and various LinkedIn generated updates. It is therefore easy to have your content deeply buried in your followers’ streams. There are certainly benefits in posting earlier in the week (which I am violating here by writing this on a Saturday). Furthermore, marketing departments have an advantage over individual posters because they can task the sales force with liking and commenting on the original post. This tactic helps distribute company news and posts. It can also be used to revive older posts. A sole practitioner lacks an army of sales and marketing amplifiers.

Posts and Updates lack a discovery tool. I’m not aware of an easy way to search the Post archive (that I’m aware of) for topics. So if I write a piece on data quality, it isn’t discoverable by the general public or my followers.

There is no easy way to view historical posts by an individual. This is the most annoying thing about LinkedIn. If I read an author who is clearly a subject matter expert (SME) on a topic of interest, I can follow the SME to view her future content (minus the content I miss because I don’t obsess about viewing my social media stream), but I cannot read her prior writings. This is an annoying gap for general readers and an unconscionable gap in LinkedIn Sales Navigator. How can a sales rep claim to be engaged in Social Selling when she can’ t easily read her prospects’ archived posts? How is she to find the opening hooks and conduct account planning using LinkedIn when it traffics only in the ephemeral. The lack of a LinkedIn discovery tool within Sales Navigator is an immense blind spot. Users should be able to view postings and updates via keyword search and timeline views. They should also be able to filter by dates, category, and business metatag. There is a clear opportunity for a sales intelligence competitor to build a Google search against LinkedIn to deliver these gap tools. If Social123 can mine the LinkedIn universe through backdoor Google, then somebody should be able to provide me with a way to view, search, and filter company and executive posts on LinkedIn.

There is no automated hyperlinking within Posts similar to those in general updates. Thus, if I reference an executive or a company, it is not associated with a LinkedIn profile. The silly thing is, if somebody comments on my post, she can use LinkedIn’s automated linking. Google+ supported this internal hyperlinking at launch and Twitter provides a type ahead tool as soon as the tweeter enters an @, $, or # symbol. I shouldn’t need to send a LinkedIn message to a marketing department to say “hey, I wrote about you” and hope they promote my post. This leaves me dependent upon other parties to promote my comments and increases the likelihood that content would be tailored to please those about whom I’m commenting. A simple example, I cannot associate this post with LinkedIn and they won’t promote it because I’m not kissing the hem of their garment. On G+ or Twitter, I can still tie my ideas to their profiles. On LinkedIn, that is not the case.

There is no question that I benefit from posting on LinkedIn due to the strong user base amongst business professionals. I left G+ for LinkedIn posting as soon as it became available to the masses. Other platforms are either flighty (Facebook), abandoned (Google+), or content islands that require their own promotion (e.g. blogs). As such, I will continue to post on LinkedIn while recognizing its faults.

Back in July, Fliptop was criticizing its competitors in the predictive analytics space for lack of pricing transparency. Their competitors (Lattice Engines and Mintigo) responded that their products were simply too complex to post prices publicly; Fliptop was a simpler offering targeting the SMB space.

A few weeks later, Fliptop again went on the offensive noting their usability stating “Fliptop has done away with the Wizard of Oz approach to predictive analytics taken by most predictive vendors (‘pay no attention to the man behind the curtain’).”

It was all shaping up to be an interesting case of marketing jujitsu until LinkedIn stepped in and bought Fliptop for its talent.

I mentioned this anecdote because it fit perfectly with a recent study by Robert J Moore of RJMetrics that analyzed pricing transparency in the martech space. Moore found that only forty percent of marketing technology companies post pricing on their website. According to Moore, “companies justify their lack of public pricing based on solution complexity — there are too many factors, they say, that go into a price. These solutions instead offer demos or ‘contact us’ forms.”

Backbone services such as CRM, marketing automation, and ecommerce are most likely to post pricing while middleware services such as data management, tag management, and identity management are the least likely to provide details.

Companies with freemium models are much more likely to provide pricing, but only 16% of the martech firms offered a free baseline service.

Moore found that companies with freemium models are more likely to have a lower paid first tier than companies that eschew freemium pricing. Non-freemium vendors generally have their lowest tier pricing 2X to 5X that of freemium vendors. Freemium vendors averaged $100 per month for their lowest tier while non-freemium vendors were slightly above $250 per month.

If you’re a vendor and want to quote pricing publicly, the data is clear: most of your competitors are quoting in monthly terms. And they’re probably doing it for a reason.
– Robert J Moore of RJ Metrics

Moore also found that monthly pricing dominates with fewer than 15% of companies advertising annual or one-time prices. The dominance of monthly pricing held across all five martech sectors. As Moore noted, this pricing is for vendors with transparent pricing; annual pricing is much more likely to be quoted by non-pricing transparent vendors when assembling a detailed quote.

The study was based upon the 1,876 company Marketing Technology Landscape put together by Scott Brinker. RJMetrics employed Amazon’s Mechanical Turk to collect the data.